Abstract : Expert reasoning in the natural sciences appears to make extensive use of a relatively small number of general principles and reasoning strategies, each associated with a larger number of more specific inference patterns. Using a dual declarative hierarchy to represent strategic and factual knowledge, we analyze a framework for a robust scientific reasoning engine. It is argued that such an engine could provide the ability to reason from basic principles in the absence of directly applicable specific information, principled knowledge acquisition by using existing general patterns to structure new information, and congenial explanation and instruction in terms of general and familiar patterns of inference.